A Spatial Prediction-Based Motion-Compensated Frame Rate Up-Conversion

Abstract

In Multimedia Internet of Things (IoT), in order to reduce the bandwidth consumption of wireless channels, Motion-Compensated Frame Rate Up-Conversion (MC-FRUC) is often used to support the low-bitrate video communication. In this paper, we propose a spatial predictive algorithm which is used to improve the performance of MC-FRUC. The core of the proposed algorithm is a predictive model to split a frame into two kinds of blocks: basic blocks and absent blocks. Then an improved bilateral motion estimation is proposed to compute the Motion Vectors (MVs) of basic blocks. Finally, with the spatial correlation of Motion Vector Field (MVF), the MV of an absent block is predicted based on the MVs of its neighboring basic blocks. Experimental results show that the proposed spatial prediction algorithm can improve both the objective and the subjective quality of the interpolated frame, with a low computational complexity.